As the autonomy of uncrewed systems advances, there is increasing demand for robust operation in complex environments. In the maritime domain, the dynamic and unstructured nature of the ocean poses significant challenges for uncrewed surface vehicles (USVs) to respond in real time using conventional optimization-based methods. This paper proposes a behavior-based control framework built from simple, modular behaviors. Each behavior is formulated as a real-valued objective function over a shared action space, and the behaviors are combined through task composition using lattice-algebraic operations―disjunction, conjunction, and negation. This approach yields a scalable arbitration scheme that integrates new behaviors by accounting for their logical interrelationships. The performance of the framework was validated through 1,000 Monte Carlo trials of an integrated multi-agent scenario combining formation maintenance, multi-target rescue, and static obstacle avoidance. Compared to a baseline that aggregates the same behaviors by a weighted sum, the proposed method reduces the root-mean-square (RMS) position error from 31.63 m to 22.78 m, raises the rescue rate from 81.74% to 90.32%, and reduces the collision rate from 4.56% to 0.85%, with non-overlapping 95% confidence intervals on every metric. The proposed architecture offers a reliable and scalable control solution for multi-objective USV operations.
This study aimed to evaluate the performance of existing wave absorbers in the KRISO ocean engineering basins and to develop an improved design that enhances wave absorption while maximizing usable basin space. Experimental measurements and potential theory calculations were performed to determine the reflection coefficients, applying linear and nonlinear damping models to perforated plates. A multi-domain boundary element method was employed to incorporate these damping models and evaluate various plate configurations. The measured reflection coefficients in both basins were approximately 0.2. For the ocean engineering basin, removing the rear vertical absorber produced negligible changes except in the long-wave region. Analytical results indicated that a double-plate configuration with an inclination angle of 11°–13° and an inter-plate spacing of approximately 0.8 m yielded the lowest reflection coefficient, which was further improved by adopting a parabolic plate profile. These findings demonstrate that an optimized, parabolic double-plate wave absorber can reduce wave reflection substantially and improve basin space utilization. Future computational fluid dynamics analyses and experiments will be conducted to determine the final absorber configuration.
Green shipping corridors have emerged as a key strategy for maritime decarbonization in response to the International Maritime Organization’s greenhouse gas reduction goals. This study conducted a preliminary feasibility assessment of alternative marine fuel use on the Korea–U.S. route. A 16,000-TEU-class container ship was considered under four fuel scenarios: heavy fuel oil (HFO), liquefied natural gas (LNG), methanol, and biodiesel. Environmental performance was evaluated on the basis of tank-to-wake CO2 emissions, a voyage-based carbon intensity indicator, and using a simplified assessment based on greenhouse gas fuel intensity, while economic performance was assessed on the basis of fuel costs and estimated regulatory costs. Under the assumptions and target values adopted in this study, LNG exhibited the lowest CO2 emissions and the most favorable estimated total operating cost. Methanol also reduced CO2 emissions relative to HFO but showed less favorable economic performance than LNG. These findings highlight the importance of integrated assessments that consider fuel characteristics, operational performance, and regulatory effects when planning green shipping corridors. Future research should incorporate well-to-wake emissions and other relevant greenhouse gases to provide a more comprehensive evaluation of alternative marine fuels.
As environmental regulations from the International Maritime Organization (IMO) become increasingly stringent, the adoption of liquefied natural gas (LNG)-fueled vessels has accelerated, highlighting the need for safe and efficient LNG bunkering infrastructure. To ensure secure simultaneous operations (SIMOPS) during bunkering, it is essential to evaluate the hydrodynamic loads exerted on moored ships by passing vessels in confined waters. This study investigated these interactions using a computational fluid dynamics (CFD) approach. Unsteady Reynolds-Averaged Navier–Stokes simulations with an overset mesh, implemented in STAR-CCM+, were validated against benchmark model test data obtained from the International Conference on Ship Manoeuvring in Shallow and Confined Water. The numerical analysis examined surge, sway, and yaw responses of moored ships, along with free-surface elevations and pressure distributions. Parametric studies systematically explored the effects of passing ship speed, lateral clearance, water depth, and quay wall gap. The results show that hydrodynamic loads increase sharply with higher passing speeds, shallower water depth, and reduced separation distances, while quay wall effects remain relatively minor. These findings demonstrate that moored ship safety is highly sensitive to operational and geometric parameters of passing ships. This research provides quantitative insights for developing practical design and operational guidelines to ensure safe SIMOPS in ports.
Robust underwater object detection and relative navigation remain challenging because of the severe degradation of sonar imagery caused by acoustic noise and artifacts. Although imaging sonar provides a viable sensing modality in GPS-denied underwater environments, its effectiveness is limited by low signal-to-noise ratios, multipath interference, and domain-dependent intensity distortions that hinder reliable feature extraction. This paper presents a simulation-aided unpaired image translation framework for enhancing sonar-based perception and navigation. The proposed method uses an unpaired image translation technique for mapping from noisy real sonar images to a noise-suppressed target domain constructed from simulated sonar images with controlled noise characteristics, without requiring paired training data. The translated images were processed using an object detector, and the resulting detections were incorporated as landmark observations within a landmark-based relative navigation framework. The experimental results with real sonar data show that the proposed approach substantially reduces false detections, leading to significantly improved detection precision and trajectory estimation accuracy compared to applying detection directly on raw sonar images. These results confirmed that simulation-aided perception can effectively bridge the domain gap in sonar-based underwater navigation without requiring paired training data.
Mooring systems for modular floating structures (MFSs) in shallow water require designs that account for a limited water depth, restricted footprint, and coupled responses among floaters, connectors, and mooring lines. This study aimed to identify an effective mooring design for an MFS under shallow-water constraints. Time-domain simulations were performed using OrcaFlex, and the numerical model was validated against the model test results for a 1×2 MFS with hinge and rigid connectors. Extreme loads corresponding to a 100 year return period were applied under collinear wave, wind, and current conditions. The mooring-line length, nominal diameter, spread angle, footprint, clump weight, and connector type were examined. The results showed that the maximum offset varied monotonically with the line length and diameter, whereas the maximum mooring tension exhibited a nonlinear behavior due to snap loads. A spread angle of = 30° provided a balanced performance by limiting excessive motion and maintaining structural safety. Clump weights reduced the required footprint by up to 76%, although they slightly increased the mooring tension. The spring–fender connector reduced excessive motions and peak tensions when compared with those observed with the hinge connector. These findings support an integrated mooring-design approach for shallow-water MFSs.
The maritime sector accounts for approximately 3% of global CO2 emissions, and stricter regulations under the International Maritime Organization greenhouse gas strategy and the European Union Emissions Trading System are accelerating the demand for mitigation technologies. Onboard carbon capture and storage (OCCS) can reduce emissions from existing vessels without fuel switching; however, design criteria for post-capture liquefaction remain unclear. This paper reviews recent literature, industrial reports, and demonstration cases related to OCCS liquefaction and storage. The information was organized around three design challenges: impurity removal, liquefaction conditions including pressure and refrigerant selection, and liquefied natural gas (LNG) cold energy utilization. Each challenge was evaluated in terms of safety, energy demand, process simplicity, and operational feasibility. The results show that onboard impurity removal should target components that limit liquefaction and storage stability, whereas stringent product specifications are better addressed onshore. A liquefaction pressure of approximately 15 bar is identified as a practical option, considering energy consumption, storage stability, and equipment burden. Refrigerant selection requires a balanced consideration of efficiency, safety, and environmental regulations, and LNG cold energy can reduce refrigeration power, though auxiliary cooling is still required to manage operational variability. This paper provides practical design criteria for shipboard OCCS liquefaction systems.
The buoyant leg storage and regasification platform (BLSRP) is a compliant offshore structure for liquefied natural gas (LNG) storage and regasification in deep waters. Although the hinged deck–leg arrangement improves structural performance, severe environmental loading may induce excessive radial leg motion and associated deck heave, affecting operational safety. To address this issue, a passive linear spring–based response control mechanism (LS-RCM) is proposed to limit the inward–outward radial motion of the buoyant legs, thereby indirectly suppressing excessive deck heave without altering the inherent compliant characteristics of the platform. Time-domain simulations incorporating irregular waves, current, and wind were performed in ANSYS AQWA for moderate, high, and very high sea states. Power spectral density analyses showed consistent suppression of heave response peaks with negligible shifts in dominant response frequencies. Phase-plot trajectories became more compact, indicating improved recentering behavior and enhanced dynamic stability. The LS-RCM also reduced response variability, with the deck-heave standard deviation decreasing from 1.141 m to 0.621 m under the very high sea state at 0° wave approach under wave-alone loading. Furthermore, buoyant-leg responses demonstrated a more balanced distribution of radial deformation under controlled conditions. The proposed LS-RCM provides an effective passive strategy for enhancing the operational safety and stability of BLSRP systems without requiring external power input.
This paper presents a computational method for determining the planar static equilibrium of a tether cable subjected to a uniform current and constant-velocity vehicle motion, to support design analysis and ensure the safe operation of tether management system (TMS)–remote-operated vehicle (ROV) systems. The tether cable was modeled as an inextensible, torsion-free element subjected to distributed loads, including its effective self-weight and hydrodynamic forces. The governing equations were formulated as a boundary-value problem in which the positions of both cable endpoints were prescribed. The hydrodynamic forces were evaluated using computational fluid dynamics (CFD) simulations conducted over a range of current velocities, cable diameters, and inflow angles from 0° to 90°. The CFD results were synthesized and parameterized as drag and lift coefficients that depend on the local cable inclination angle and were subsequently approximated with polynomial models to enable efficient evaluation during the static analysis. The resulting nonlinear boundary-value problem was solved using a Newton iterative method. The proposed approach enabled rapid predictions of the cable geometry and tension distribution, providing an effective tool for static analysis and operational planning of ROV systems under steady-current conditions and constant-velocity vehicle motion.
In recent years, the Kilo 5 Beach area of Banggai Regency, Central Sulawesi, Indonesia, has experienced hydrodynamic pressure leading to coastal abrasion. This study analyzed the effectiveness of low-crested breakwaters (LCB) constructed using Geotube materials in reducing wave energy and enhancing sediment accretion at Kilo 5 Beach. The method used was an integrated approach that comprehensively combined field data, sediment characteristics, bathymetry, and numerical hydrodynamic modeling. The numerical simulations showed that the low-threshold breakwater structure could reduce the average wave energy by 76%, enhance sediment deposition, and support natural accretion processes behind the breakwater structure. Morphodynamic simulations showed sediment accretion of up to 20 m behind the structure, while localized erosion of up to 15 m occurred around the gaps and sides of the structure due to flow acceleration. These findings show that low-crested breakwaters are effective in redistributing the hydrodynamic energy and accelerating shoreline stabilization and natural reclamation. Nevertheless, the potential for localized scouring at the toe of the structure must be considered in the technical design. Overall, low-crested breakwaters represent an adaptive and environmentally friendly alternative for coastal protection against abrasion, particularly in semi-enclosed tropical coastal areas.
Preventing accidents during crane operations in shipyards requires a decision support system that adapts to rapidly changing weather conditions. Strong winds and gusts significantly increase the risk of accidents during hoisting and lowering tasks, making a quantitative, weather- informed safety assessment essential. To enable such assessments, real-time data from the Korea Meteorological Administration (KMA) Automatic Weather System (AWS) were used to visualize the wind speed and direction across the shipyard through a responsive map interface. In parallel, a Unity 3D-based multibody dynamics simulation environment was constructed to evaluate the operational safety of jib cranes under diverse wind scenarios. The integrated system delivers guidance on operational limits, gust condition simulations, wind warning notifications, collision detection, and automated emergency stop alerts, supporting safer and more efficient decision making for both operators and managers. Since the architecture is aligned with real shipyard workflows, it can be readily extended to other crane types and work processes. The outcomes of this work are expected to contribute to the realization of smart yards and to advance digital twin-based safety management systems.
The growing concerns about greenhouse gas (GHG) emissions from ships have drawn attention to various methodologies and indices developed for the standardised assessment of these emissions. However, existing approaches fail to account for the full life cycle of ships, focusing exclusively on marine fuels. This study introduces a ship-oriented GHG assessment methodology and its corresponding index, the Ship Life cycle Greenhouse gas Intensity (SLGI). This framework evaluates the entire life cycle of a ship, spanning from raw material production and shipbuilding to operations and decommissioning. A comparative analysis alongside existing indices is conducted on three case studies involving transitions to alternative marine fuels driven by technological advancements and strengthening regulations. The results show that while the absolute GHG emissions decrease as fuel transition takes place, the limited scope of current measures leads to unreliable assessment outcomes. In particular, the progressive increase in the upstream emission share from non-fuel materials, which were previously overlooked, indicates a potential for shifting the emission burden. Therefore, this study demonstrates the inherent limitations of existing GHG assessment measures for ships and the necessity of a ship-oriented approach based on a life cycle perspective for precise evaluation.
Understanding sea-state dynamics along the northern Atlantic coast of Morocco is essential for coastal planning because wave transformation plays a key role in the nearshore energy distribution, harbor agitation, and navigation conditions. This study developed and applied a multi-scale modeling framework to simulate wave propagation from offshore to harbor scale and assess wave conditions at Larache Port, Morocco. The methodology was based on a nested numerical framework combining TOMAWAC, TELEMAC-2D, and ARTEMIS to simulate wave propagation from the offshore to the harbor scales. Sensitivity analyses examined the effects of mesh resolution, frequency, and directional discretization, and source-term parameterization on wave predictions. The transfer of boundary conditions between models was refined using the Miche and Ursell criteria to ensure consistent nesting across offshore, nearshore, and harbor domains. The results suggested that nonlinear triad interactions exert a dominant influence on nearshore wave predictions, whereas quadruplet interactions and whitecapping have a weaker effect in the study area. The coupled simulations also showed that tidal currents significantly affect the significant wave height and mean wave direction. Moreover, the refined TOMAWAC–ARTEMIS interface improved the representation of diffraction and harbor agitation within the basin. Overall, the framework offers a robust methodology for improving coastal resilience along the Atlantic coast of Morocco.
Barge transportation using tug–barge systems is widely employed for large cargo transport in rivers and harbor areas, where maneuverability in confined waterways is critical. This study numerically investigates the maneuvering performance of tug–barge systems under pushing and towing operations. Simulations were conducted using a maneuvering model based on the Maneuvering Mathematical Modeling Group framework with experimentally derived hydrodynamic coefficients for each operation mode. For pushing operations, barge configurations were varied by changing the numbers of barges in the longitudinal and transverse directions, whereas for towing operations, the effects of skeg attachment and towline length were examined through turning simulations. The results show that increasing the number of barges generally degrades turning performance, and longitudinal extension causes a greater increase in turning radius than transverse extension. In towing, skeg attachment reduces turning performance by increasing yaw damping and restoring moment, whereas longer towlines enlarge the turning radius by producing a greater negative yaw moment on the tug. Overall, towing yields smaller drift angles and greater rudder effectiveness than pushing, indicating superior turning performance in confined waterways.
Liquid hydrogen (LH2) storage tanks are essential for long-range hydrogen transport and mobility, but their performance is controlled by coupled heat ingress, phase change, stratification, ullage pressure evolution, and motion-induced interface renewal. This review synthesizes the thermophysical fundamentals, tank architectures, insulation systems, quiescent storage behavior, operational transients, sloshing-coupled cryogenic dynamics, diagnostics, modeling hierarchies, and safety and approval requirements, with the fill ratio treated as a central design variable. The literature is organized through an evidence taxonomy spanning direct operation, controlled LH2 experiments, transitional evidence, and simulation-only studies. Three synthesis findings emerged. First, the fill ratio and motion jointly determine ullage stratification, wetted-wall distribution, and interfacial renewal so that intermediate-fill operation can trigger either boil-off amplification or short-duration pressure collapse. Second, mobility-relevant design cannot rely solely on quiescent boil-off or sloshing-load analysis. Reliable predictions require coupled treatment of thermodynamics, motion, controls, and validation. Third, the strongest evidence comes from benchmark self-pressurization datasets, trailer-route operation, and pilot-scale marine transport, whereas validation-grade motion-enabled datasets remain scarce for large maritime tanks and lightweight aviation concepts. Therefore, approval-oriented LH2 tank design should be evidence-graded, motion-aware, and explicitly linked to uncertainty-bounded verification and validation.
Marine radiological monitoring has long relied on manual seawater sampling, limiting the timeliness of environmental surveillance. This paper reports the optimization of the MARK-U3 (Monitoring of ambient radiation of KAERI-Underwater #3) buoy-type system, designed to enable fully automated seawater sampling, in situ gamma-ray spectrometry, and autonomous offshore operation. The technical requirements for improved sensitivity and stability were derived through system analysis, leading to a redesign featuring a 3 L sampling container, diaphragm pump-based overflow quantification, and a cable-winch depth-control mechanism. Field evaluations showed that increasing the sampling volume to 3 L, while maintaining the background count rate through the self-shielding effect of the seawater sample, theoretically reduced the minimum detectable activity (MDA) by approximately 1.3. Crucially, the structural reinforcement with ballast weights ensured vertical stability, maintaining a constant measurement geometry compared to the detector even under wave-induced motion. In addition, the automated cleaning module successfully eliminated cross-contamination. These results showed that the optimized MARK-U3 system is well-suited for routine marine radiological surveillance and rapid emergency-response applications.
Although tsunami-driven drifting debris poses a critical secondary hazard to coastal infrastructure, quantifying the resulting impact forces is challenging because of the limited post-event observations and a lack of full-scale experimental data. This paper presents a coupled numerical framework integrating a numerical wave tank (NWT) with LS-DYNA to estimate the debris-induced impact forces under tsunami-like inundation conditions. The NWT was used to simulate wave generation, propagation, overtopping, and the resulting nearshore hydrodynamics. In contrast, the arbitrary Lagrangian–Eulerian (ALE) formulation in LS-DYNA was used to resolve debris transport and collision dynamics. Validation against existing hydraulic experiments showed that the proposed framework captures the overall sequence of debris drift and collision reasonably well. Nevertheless, some discrepancies remain in the drift initiation and collision velocity because of the simplified representations of friction and contact. The results further suggest that local contact conditions during collision and the momentum characteristics of the inundation flow strongly influence the maximum impact force. The proposed framework provides conservative estimates of debris-induced impact forces because the numerical model tends to produce surface-to-surface collisions owing to suppressed rotational motion. Overall, the coupled NWT–LS-DYNA framework provides a rational and conservative basis for assessing debris-collision hazards and supporting the structural design of tsunami-prone coastal infrastructure.
Natural gas installation systems involve complex technical, organizational, and human interactions where failures can lead to catastrophic safety consequences. Conventional Failure Mode and Effects Analysis (FMEA) is constrained by subjective scoring and the limited capture of systemic variability. This paper proposes an integrated framework combining the Functional Resonance Analysis Method (FRAM), fuzzy logic-based FMEA, and Pareto analysis to address these limitations. FRAM was applied to model system functions and identify variability sources across installation stages, which were translated into candidate failure modes. A multidisciplinary expert panel evaluated the occurrence, severity, and detection scores for each failure mode. A Mamdani-type fuzzy inference system was then used to calculate the fuzzy Risk Priority Numbers (RPNs), and Pareto analysis was applied to prioritize critical failure modes. The framework was validated in a real building natural gas installation project, identifying 81 failure modes. Fuzzy-FMEA produced substantially different risk rankings than classical FMEA. Specifically, improper tightening of valve connection points emerged as the highest-risk failure mode. Pareto analysis showed that 52 failure modes (64.2%) account for 80% of the cumulative system risk. The proposed framework enhances the completeness of failure identification and the reliability of risk prioritization, providing a systematic decision-support tool for natural gas installation safety management.
Autonomous ships require reliable situational awareness to ensure safe navigation, particularly during collision avoidance in congested maritime environments. Although an automatic identification system (AIS) is widely used for vessel traffic awareness, its update intervals, communication delays, and measurement noise introduce positional uncertainty, which limits its direct application to real-time collision avoidance. This study aims to develop a collision avoidance framework that incorporates AIS-derived position uncertainty from the perspective of an autonomous ship. An unscented Kalman filter is applied to estimate the nonlinear motion and positional uncertainty of surrounding vessels in real time to compensate for information gaps in AIS data. Using the predicted vessel states, collision risk is quantitatively evaluated through a collision risk index, and avoidance maneuvers are generated using the velocity obstacle method. The framework is validated through simulations in which positional uncertainty is introduced deliberately, and vessel maneuvering behavior is represented using a dynamic model derived from the maneuvering modeling group theory. Simulation results show that the proposed system improves the consistency of collision risk assessment and estimates target vessel trajectories with an average positional accuracy of ~3 m. This corresponds to an ~96% reduction in estimation error compared to that obtained using nonpredictive approaches.
